Research Associate (Engineering/Electrical & Material)

Nanyang Technological University; Singapore; On-site; SGD 45,000 - 65,000; Full time

Job summary

Nanyang Technological University’s NTI-NTU Corporate Laboratory invites applications for a Research Associate to analyze equipment degradation time-series data and develop forecasting workflows using statistical, machine learning, and deep learning models.

You will work with researchers and engineers to preprocess data, apply forecasting methods, evaluate performance, and communicate insights that support predictive maintenance and reliability studies.

Qualifications

• Masters in Materials Science, Electrical/Electronic Engineering, Physics, or related field.
• Strong interest or experience in data analysis and time-series modeling.
• Proficiency in Python for data processing and model development.
• Knowledge of machine learning or deep learning techniques is a plus.

Responsibilities

• Develop and apply time-series forecasting methods for semiconductor equipment health monitoring.
• Analyze equipment degradation data to support predictive maintenance and reliability studies.
• Implement and compare statistical, machine learning, and deep learning forecasting models.
• Perform data preprocessing, signal smoothing, and noise analysis on real-world equipment data.
• Evaluate model performance using forecasting metrics and visual analysis.

Skills

Time-series analysis

Data analysis

Python

Forecasting

Education

Masters in Materials Science, Electrical/Electronic Engineering, Physics, or related field

Tools

Python

Job description

NTI-NTU Corporate Laboratory is a collaboration between Nanofilm Technologies International Limited ("Nanofilm", "NTI"), Nanyang Technological University ("NTU") and supported by Singapore under RIE2030. The Laboratory’s objective is to propel Innovation and Technologies commercialisation through NTU’s innovation and NTI’s deep technology. NTI-NTU Corporate Laboratory aligns with Singapore’s RIE2030 handbook – which emphasises the nation’s commitment to research and innovation, aiming to drive economic growth and address national challenges. The Nanyang Technological University NTI-NTU Corporate Laboratory is seeking to hire a Research Associate. The selected candidate will focuses on analyzing equipment degradation time-series data and developing forecasting workflows using statistical, machine learning, and deep learning models.

Key Responsibilities:

Develop and apply time-series forecasting methods for semiconductor equipment health monitoring. Analyze equipment degradation data to support predictive maintenance and reliability studies. Implement and compare statistical, machine learning, and deep learning forecasting models. Perform data preprocessing, signal smoothing, and noise analysis on real-world equipment data. Evaluate model performance using appropriate forecasting metrics and visual analysis. Interpret results to determine when forecasting is meaningful and when data limitations apply. Document findings and communicate insights to researchers and engineering teams.

Job Requirements:

Masters in Materials Science, Electrical Electronic Engineering, Physics, or a closely related field. Strong interest or experience in data analysis and time-series modeling. Proficiency in Python for data processing and model development. Basic knowledge of machine learning or deep learning techniques. Ability to work with noisy, real-world datasets and interpret results critically. Good analytical thinking and clear technical communication skills. Postgraduate degree or experience in semiconductor-related research is an advantage.

We regret that only shortlisted candidates will be notified. Hiring Institution: NTU A research-intensive public university, Nanyang Technological University, Singapore (NTU Singapore) has 33,000 undergraduate and postgraduate students in the Engineering, Business, Science, Humanities, Arts, & Social Sciences, and Graduate colleges. It also has a medical school, the Lee Kong Chian School of Medicine, established jointly with Imperial College London. NTU is also home to world-class autonomous institutes – the National Institute of Education, S Rajaratnam School of International Studies, Earth Observatory of Singapore, and Singapore Centre for Environmental Life Sciences Engineering – and various leading research centres such as the Nanyang Environment & Water Research Institute (NEWRI) and Energy Research Institute @ NTU (ERI@N). Ranked amongst the world’s top universities by QS, NTU has also been named the world’s top young university for the past seven years. The University’s main campus is frequently listed among the Top 15 most beautiful university campuses in the world and has 57 Green Mark-certified (equivalent to LEED-certified) buildings, of which 95% are certified Green Mark Platinum. Apart from its main campus, NTU also has a campus in Novena, Singapore’s healthcare district. Under the NTU Smart Campus vision, the University harnesses the power of digital technology and tech-enabled solutions to support better learning and living experiences, the discovery of new knowledge, and the sustainability of resources. For more information, visit www.ntu.edu.sg About NIE About RSIS About LKCMedicine About NTUItive